Track: Artificial Intelligence

Abstract

The study literature on Artificial Intelligence and digital business models has grown in recent years. It is increasingly in contact with the discipline of digital business model science as artificial intelligence technology advances. Using bibliometric mapping, this study attempts to comprehensively evaluate research trends in digital transformation and future research potential in the area. We visualized Artificial Intelligence for Digital Business Model research published in the previous 10 years, from 2002 to 2021, using bibliometric analytic methodologies. For our investigation, 145 publications from Scopus were chosen. This study pulls data from the Scopus database, analyzes it using the Scopus online analysis function, then visualizes it using Vosviewer. The process is divided into five stages: keyword selection, first search results, search result refining, initial compilation, and data analysis. According to our major line of study, papers published by scholars in the United States have the most publications, with 28 scientific publications. The field of study “Computer Science” has the most documents, with N=91 (31.2%). The number of publications increased from 2016 to the greatest in 2021, with 33 documents. The analyzed data reveals patterns and trends in worldwide Scopus-indexed articles. The analyzed data reveals patterns and trends in worldwide Scopus-indexed articles. This study suggests merging the following research topics: computer science, implementation, technique, and education, abbreviated as CSITE research themes.